Molecular systems evaluation of oligomerogenic APP(E693Q) and fibrillogenic APP(KM670/671NL)/PSEN1(Δexon9) mouse models identifies shared features with human Alzheimer's brain molecular pathology

Abstract

Identification and characterization of molecular mechanisms that connect genetic risk factors to initiation and evolution of disease pathophysiology represent major goals and opportunities for improving therapeutic and diagnostic outcomes in Alzheimer's disease (AD). Integrative genomic analysis of the human AD brain transcriptome holds potential for revealing novel mechanisms of dysfunction that underlie the onset and/or progression of the disease. We performed an integrative genomic analysis of brain tissue-derived transcriptomes measured from two lines of mice expressing distinct mutant AD-related proteins. The first line expresses oligomerogenic mutant APP(E693Q) inside neurons, leading to the accumulation of amyloid beta (Aβ) oligomers and behavioral impairment, but never develops parenchymal fibrillar amyloid deposits. The second line expresses APP(KM670/671NL)/PSEN1(Δexon9) in neurons and accumulates fibrillar Aβ amyloid and amyloid plaques accompanied by neuritic dystrophy and behavioral impairment. We performed RNA sequencing analyses of the dentate gyrus and entorhinal cortex from each line and from wild-type mice. We then performed an integrative genomic analysis to identify dysregulated molecules and pathways, comparing transgenic mice with wild-type controls as well as to each other. We also compared these results with datasets derived from human AD brain. Differential gene and exon expression analysis revealed pervasive alterations in APP/Aβ metabolism, epigenetic control of neurogenesis, cytoskeletal organization and extracellular matrix (ECM) regulation. Comparative molecular analysis converged on FMR1 (Fragile X Mental Retardation 1), an important negative regulator of APP translation and oligomerogenesis in the post-synaptic space. Integration of these transcriptomic results with human postmortem AD gene networks, differential expression and differential splicing signatures identified significant similarities in pathway dysregulation, including ECM regulation and neurogenesis, as well as strong overlap with AD-associated co-expression network structures. The strong overlap in molecular systems features supports the relevance of these findings from the AD mouse models to human AD.

Figure 1

Schematic overview of mouse AD transcriptome analysis. RNA sequencing was performed on the entorhinal cortex and dentate gyrus for three groups of animals (oligomerogenic APP^E693Q, fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 and wild type) comprising a total of 28 samples (Transgenic n=3 and Wild type n=4 samples per comparison). Region-based differential gene and exon expression analysis was performed between all mouse lines, and results were annotated with diverse functional molecular data.

Figure 2

Differential gene expression and enrichment analysis summary. (a) Differentially expressed genes in the entorhinal cortex of oligomerogenic APP^E693Q vs wild-type mice. (b) Top differentially expressed genes in the dentate gyrus of fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mice. (c) Quantity of differentially expressed genes and selected GO term enrichments shared across regional comparisons of fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 and oligomerogenic APP^E693Q vs wild-type mice. (d) Quantity of differentially expressed genes and selected GO term and KEGG pathway enrichments shared across regional comparisons of fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice vs oligomerogenic APP^E693Q mice. Enrichments shown were selected for known or suspected relevance to AD pathophysiology, and bolding highlights enrichments that relate to the main biological themes also implicated by the differential exon analysis findings. (Differential expression and gene set enrichments thresholded at FDR<0.05.) FDR, false discovery rate.

Figure 3

Multiregion transcriptome comparisons between fibrillogenic, oligomerogenic and wild-type mice implicates amyloid/Aβ processing, extracellular matrix (ECM) regulation and neurogenesis (a, b–i) Fragile X Mental Retardation 1 (FMR1) gene is differentially spliced in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice vs oligomerogenic APP^E693Q dentate gyrus (also vs wild type), as well as multiple brain regions in LOAD and (b-ii) is a known regulator of APP, binding to mRNA in the post-synaptic neuron in an mGluR5 stimulation-dependent manner. (b-iii) DE genes in both comparisons with wild type (see Figure 2), are enriched for known protein interactors of APP. APP interactors that are DE in the fibrillogenic APP^KM670/671NL/PSEN1^Δexon9DG vs wild type are shown. (b-iv) Adaptor protein GRB2 is differentially spliced in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice vs oligomerogenic APP^E693Q dentate gyrus, and interacts with APP and PSEN1, localized to the centrosomes, resulting in ERK1/2 activation, and potentiation of oligomer-induced toxicity. (c) ECM regulation was a recurring theme of the pathway analysis following differential gene and exon expression analysis. (c-i) Known ECM regulators that are differentially expressed in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mice (dentate gyrus) suggest mechanisms of perturbation and compensation. (c-ii) Gene Ontology (GO) enrichment analysis of the 354 genes that are differentially expressed in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mice (dentate gyrus) demonstrate that the trend toward ECM disruption is particularly strong in this comparison. (d) Pathway enrichment analysis of the differentially expressed genes in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mice (dentate gyrus) indicates perturbation of stem cell, neural progenitor cell and neurogenesis pathways. (d-i) SUZ12 is a key member of the polycomb repressive complex 2 (PRC2), and is differentially spliced in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice vs oligomerogenic APP^E693Q dentate gyrus (and also vs wild type). (d-ii) A functional role for SUZ12 is strongly supported by enrichment analysis of ChipSeq-based transcription factor gene targets, with the 354 differentially expressed genes in fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mice (dentate gyrus). (d-iii) SUZ12 function within the PRC2 is associated with regulation of neurogenic differentiation of stem cells via histone H3K27 and H3K9 methylation. (e-i) Zinc finger gene SP1 was identified as the transcription factor most strongly enriched for DEX genes (APP^KM670/671NL/PSEN1^Δexon9 vs wild-type comparison). (e-ii) SP1 is a transcriptional regulator of multiple AD-associated genes, and forms a potential link between these molecular nodes and the main DEX themes we have discussed, including perturbations in neurogenesis, amyloid processing and ECM regulation.

Figure 4

Differential exon expression and enrichment analysis summary. (a) Differential exon analysis comparisons between all three mouse lines. (b) Quantity of genes with differentially expressed exons (DEX) for fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice and oligomerogenic APP^E693Q mice vs wild type. Enrichments for DEX genes in a library of curated brain-focused gene sets, highlighted for connection to Alzheimer's disease (AD), other neuropsychiatric disease (NPD) and cell/brain regional signatures (Cell) for (c) APP^E693Q oligomerogenic vs wild-type mouse entorhinal cortex and (d) fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs wild-type mouse. (e) Quantity of DEX genes for fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 mice vs oligomerogenic APP^E693Q mice across dentate gyrus (DG) and entorhinal cortex. (f) DEX genes for fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 vs oligomerogenic APP^E693Q mice in the DG, highlighted for multiple themes, including amyloid/Aβ regulation and processing (APP), association with AD risk, extracellular matrix regulation (ECM) and multiple others (MULTI). Concordance with DEX in human postmortem LOAD samples across the frontal pole (FP), superior temporal gyrus (STG) and parahippocampal gyrus (PHG) are also shown. (DEX genes with FDR<0.05 and gene set enrichments with FDR<0.1 are shown). FDR, false discovery rate.

Figure 5

Enrichments for differentially expressed genes and differentially spliced genes with human LOAD signatures. (a) Similarity of AD model transcriptional changes with postmortem LOAD gene expression collected from six brain regions (AD vs non-demented controls). Spearman's rho (shown in heatmap cells) reflects correlation between log2 fold change of orthologous mouse-human genes. All correlations were positive and significant. (b) Gene co-expression modules constructed from human postmortem brain samples (AD and non-demented controls) were intersected with DE and DEX gene sets, identifying multiple significant overlaps, including modules that are significantly differentially connected in LOAD. (c) Bayesian network built from human LOAD postmortem prefrontal cortex samples, subset by fibrillogenic APP^KM670/671NL/PSEN1^Δexon9 DE genes (FDR<0.1), and their immediate neighbors. TYROBP, the key driver in the subnetwork most strongly associated with LOAD status, remained the most strongly connected gene in this induced subnetwork and is shown here with its local network neighborhood (first and second degree neighbors). (DE and DEX genes with FDR<0.05 -unless otherwise stated- and gene co-expression module enrichments with FDR<0.1 are shown). FDR, false discovery rate.